Tag Archives: evolutionary psychology

Nicholas Wade, former science reporter for the New York Times has written a book, A Troublesome Inheritance, in which he argues that large-scale societal differences (e.g., the existence of capitalist democracies in the West or of paternalistic, authoritarian political systems in Asia) may be attributable to small genetic differences that were fixed at a population level through the action of natural selection since the emergence of anatomically modern humans and their subsequent dispersal from Africa. The fixation of these gene variants happened because the continents of Europe, Asia, and Africa (homes of the major “racial” groups) differed in systematic ways. David Dobbs recently reviewed it in the Sunday Review of Books, which prompted a kind of amicus brief letter-to-the-editor from over 120 population geneticists, affirming that Wade’s writing misrepresents the current science of genetics. A full list of the signatories of this letter can be found here. It is a veritable who’s who of contemporary population genetics.

As you might imagine, A Troublesome Inheritance has been quite controversial. A great deal has already been written on this book, both in formal publications and in the science (and economics) blogging ecosystem. To name just a few, Greg Laden, my old homie and fellow TF for Irv DeVore‘s famous Harvard class, Science B-29, Human Behavioral Biology, wrote a brief review here for American Scientist. Columbia statistician and political scientist, Andrew Gelman, wrote a review for Slate.com. Notre Dame professor and frequent contributor of popular work on human evolution, Agustin Fuentes, wrote a critique for Huffington Post, while UNC-C anthropology professor Jonathan Marks wrote a critique for the American Anthropological Association blog, which also appears in HuffPo.

Honestly, I think that Wade’s book is so scientifically weak and ideological (despite his protestations that science should be apolitical) that it is likely to have a very short half-life in contemporary discourse on human diversity and science more broadly. In fact, I have advocated to the editorial boards of professional societies to which I belong not to do anything special about this book since I’m confident it will be soon forgotten for its sheer scientific mediocrity. I find it interesting that the great majority of the people who like the book seem not to be scientists but comment on Wade’s “bravery” for spurning “political correctness” and the like. There are substantial parallels here to public debate over climate change or vaccination: the professional conclusions of the scientists who actually work on the topic only matter when they correspond with the social, political, or economic interests of the parties engaging in the debate. What do geneticists know about genetics anyway? So, it is with some hesitancy that I write about it, but my colleagues’ letter has reminded me of a larger beef I have with the contemporary state of human evolutionary studies. This beef boils down to the fact that most contemporary students of human evolutionary biology know next to nothing about genetics. I’ve actually encountered a number of leading figures in human behavioral biology who maintain an outright hostility toward genetics. This is a topic that my colleague Charles Roseman and I have grumbled about for a few years now. We keep threatening to do something about it, but haven’t quite gotten around to it yet. Perhaps this is a humble start…

This state of affairs is extremely problematic since genetics is the material cause (in the Aristotelean sense) or one of the mechanistic causes (in the Tinbergian sense) of much of the diversity of life. If we are going to make a scientific claim that some observed trait is the result of natural selection, we should be able to have a sense for how such a trait could evolve in the first place. The standard excuse for ignoring genetics in the adaptive analysis of a trait of interest is what Alan Grafen termed the “phenotypic gambit.” The basic idea behind the phenotypic gambit is that natural selection is strong enough to overcome whatever constraints may be acting on it. The phenotypic gambit is a powerful idea and it has yielded some productive work in behavioral ecology. I use it. However, a complete evolutionary explanation of a trait’s existence needs to consider all levels of explanation. In modern terms, and as nicely outlined a letter by Randolph Nesse, we need to answer questions about mechanism, ontogeny, phylogeny, and function. Explanations relying on the phenotypic gambit only address the functional question (i.e., fitness, or what Tinbergen called the “survival value” of the trait).

I could go on about this for a long time, so I will limit myself to three points: (1) complex traits will generally not be created by a single gene, (2) heritability and the response to selection are regularly misunderstood and misapplied, (3) we need to think about the strength of selection and the constancy of selective regimes when making statements about the adaptive evolution of specific traits.

First, we need to get over the whole one-gene thing. Among other things, the types of adaptive arguments that are made particularly for recent human behavioral innovations are simply highly implausible for single genes. There are a variety of formulae for calculating the time to fixation of advantageous alleles that depend on the particulars of the system (e.g., details about dominance, initial frequency, mutation rate). Using the approximation that the number of generations that it takes for the fixation of a highly advantageous allele with selection coefficient is simply twice the natural logarithm of divided by , we can calculate the expected time to fixation for an advantageous allele. With a (very) substantial average selection coefficient of (think of lopping of 5% of the population each generation), the time to fixation of such a highly advantageous allele is about 120 generations generations. That’s over 3,000 years for humans. This is interesting, of course, because it makes the type of recent evolution the John Hawks or Henry Harpending have discussed more than plausible. It makes it hard to imagine how the large changes in presumably complex behavioral complexes in historical time suggested by authors such as Wade or Gregory Clark, author of Farewell to Alms (which I actually find a fascinating book), pretty implausible.

In addition to the population-genetic implausibility of single-locus evolutionary models, complex traits are polygenic, meaning that they are constructed from multiple genes, each of which typically has a small effect. Now, this doesn’t even address the issue of epigenetics, where genotype-environment interactions profoundly shape gene expression and can produce fundamentally different phenotypes in the absence of significant genetic difference, but that’s another post. In many ways, this is good news for people who study whole organisms in a naturalistic context (like human behavioral ecologists!) because it means that we can work with quantitatively-measured trait values and apply regression models to understanding their dynamics. In short, the math is easier though, admittedly, the statistics can be pretty tricky. Further good news: there are lots of people who would probably be happy to collaborate and there are plenty of training opportunities in quantitative genetics through short courses, etc.

The masterful review paper that Marc Feldman and Dick Lewontin wrote for Science in 1975 amid the controversy surrounding Arthur Jensen’s work on the genetics of intelligence, and its implications for racial educational achievement differentials, still applies. Heritability is a systematically misunderstood concept and its misuse seems to surface in policy debates approximately every twenty years. Heritability, in the strict sense, is a ratio of the total phenotypic variance that is attributable to additive genetic variance (i.e., the variance contributed by the mean effect of different alleles). Because total variance of the phenotype is in the denominator of this ratio, heritability is very much a population-specific measure. If a population has low total phenotypic variance because of a uniformly positive environment, for instance, there is more potential for a greater fraction of the total variance to be due to additive genetic variance. Think, for example, about children’s intelligence (as measured through psychometric tests) in a wealthy community with an excellent school district where most parents are college-educated and therefore have the motivation to guide their children to high scholastic achievement, the resources to supplement their children’s school instruction (e.g., hiring tutors or sending kids to enrichment programs), and the study skills and knowledge base to help their children with homework, etc. I have used this example in prior post. Given the relative uniformity of the environment, more of the variation in test scores may be attributable to additive genetic contributions and heritability would be higher than it would be in a more heterogeneous population. This is a hypothetical example, but it illustrates the rather constrained meaning of heritability and the problems associated with its application to cross-population comparisons. It is also suggestive of the problem of effect sizes of different contributions to phenotypic variance. The potential for environmental variance to swamp real additive genetic variance is quite large. What’s a better predictor of life expectancy: having a genetic predisposition to high longevity or living in a neighborhood with a high homicide rate or a endemic cholera in the drinking water supply?

Heritability essentially measures the potential response to selection, everything else being equal. The so-called Breeder’s Equation (Lush 1937) states that the change in a single quantitative phenotype (e.g., height) from one generation to the next is equal to the product of heritability and the force of selection. If there is lots of additive variability in a trait but not much selective advantage to it, the change in the mean phenotype will be small. Similarly, even if selection is very strong, the phenotype will not change much if the amount of additive variance is low. A famous, but frequently misunderstood result, known as Fisher’s Fundamental Theorem shows that the change in fitness is directly proportional to variance in fitness. This is really just a special case of the breeder’s equation, as shown in great detail in Lynch and Walsh’s textbook (and their online draft chapter 6) or in Steve Frank’s terrific book, in which the trait we care about is fitness itself. An important implication of Fisher’s theorem is that selection should deplete variance in fitness — and this makes sense if we think of selection as truncating a distribution. A corollary of Fisher’s theorem is that traits which are highly correlated with fitness should not have high heritability. Oops. Does this mean that intelligence, with its putatively very high heritabilities is not important for fitness?

Everything in the last paragraph applies to the case where we are only considering a single trait. When we consider the joint response of two or more traits to selection, we must account for correlations between traits (technically, additive genetic covariances between the traits). Sometimes these covariances will be positive; sometimes they will be negative. When the additive genetic covariance between two traits is negative, it means that selection to increase the mean of one will reduce the mean of the other. In their fundamental (1983) paper, my Imperial College colleague Russ Lande and Steven Arnold generalized the breeder’s equation to the multivariate case. The response to selection becomes a balancing act between the different force of selection, additive genetic variance, and additive genetic covariance for all the traits. Indeed, this is where constraints come from (or it’s at least one place). Suppose there are two traits (1 and 2) that share a negative covariance. Further suppose that the force of selection is positive for both but is stronger on trait 1 than it is on trait 2. Depending on the amount of genetic variance present, this could mean that the mean of trait 2 will not change or even that the mean could decrease from one generation to the next.

The work of Lande and Arnold (and many others) has spawned a huge literature on evolvability (something that Charles has moved into and that we have some nascent collaborative work on in the area of human life-history evolution). This work is very important for understanding things like the evolution of human psychology. Consider the hypothesis, popular in evolutionary psychology, that the mind is divided into a large number of specific problem-solving “modules,” each of which is the product of natural selection on the outcome of the problem-solving. How do you create so many of these “organs” in a relatively short time frame? Humans last shared a common ancestor with chimpanzees and bonobos around five million years ago and most likely human ancestors until about 1.8 million years ago seem awfully ape-like (and therefore probably not carrying around anything like the human mental toolkit in their heads). One of the key processes responsible for the creation of complex phenotypes is known as modularity (which is a bit confusing since this is also the term that evolutionary psychologists use for these mental organs!) and one of the fundamental mechanisms by which modularity is achieved is through the duplication of sets of genes responsible for existing structures. These duplicated “modules” are less constrained because of their redundancy and can evolve to form new structures. However, the fact that modules are duplicated means that they should experience substantial genetic correlation with their ancestral modules. This makes me skeptical that the diversity of hypothetical structures posited by the massive modularity hypothesis could be constructed by directional selection on each module. There is just bound to be too much correlation in the system to permit it to move in a fine-tuned way toward to phenotypic optimum for each module.

Trade-offs matter for the evolution of phenotypes. While I suspect that very few human evolutionary biologists would argue with that, I think that we generally fall short of considering the impact of trade-offs for adaptive optima. The multivariate breeders’ equation of Lande and Arnold gives us an important (though incomplete) tool for looking at these trade-offs mechanistically. A few authors have done this. The example that comes immediately to mind is Virpi Luumaa and her research group, who have done some outstanding work on the quantitative genetics of human life histories using Finnish historical records.

My third, and last (for now), point addresses the constancy of selection. This is related to the concept of the Environment of Evolutionary Adaptedness (EEA), central to the reasoning of evolutionary psychology. A few years back, I wrote quite a longish piece on this topic and its attendant problems. Note that when we use population-genetic models like the one we discussed above for the expected time to fixation of an advantageous allele, the selection coefficient is the average value of that coefficient over time. In reality, it will fluctuate, just as the demography of the population selection is working on will vary. Variation in vital rates can have huge impacts on demographic outcomes, as my Stanford colleague Shripad Tuljapurkar has spent a career showing. It can also have enormous effects on population-genetic outcomes, which shouldn’t be too surprising since it’s the population of individuals which is governed by the demography that is passing genetic material from on generation to the next!

When I read accounts of rapid selection that rely heavily on EEA-type environments or the type of generalizations found in the second half of Wade’s book (e.g., Asians live in paternalistic, autocratic societies), my constant-environment alarm bells start to sound. I worry that we are essentializing societies. One of the all-time classic works of British Social Anthropology is Sir Edmund Leach’s groundbreaking Political systems of Highland Burma. Leach found that the social systems of northern Burma were far more fluid than anthropologists of the time typically thought was the case. One of the key results is that there was a great deal of interchange between the two major social systems in northern Burma, the Kachin and and Shan. Interestingly, the Shan, who occupied lowland valleys, practiced wet-rice agriculture, and whose social systems were highly stratified were seen by western observers as being more “civilized” than the Kachin, who occupied the hills, practiced slash-and-burn agriculture, and had much more egalitarian social relations. Leach (1954: 264) writes, “within the general Kachin-Shan complex we have, I claim, a number of unstable sub-systems. Particular communities are capable of changing from one sub-system into another.” Yale anthropologist/political scientist James Scott has extended Leach’s analysis in his recent book, The Art of Not Being Governed, and suggested that the fluid mode of social organization, where people alternate between hierarchical agrarian states, and marginal tribes depending on political, historical, and ecological vicissitudes is, in fact, the norm for the societies of Southeast Asia.

The clear implication of this work for our present discussion is that a single lineage may find some of its members struggling for existence in hierarchical states where the type of docility that Wade suggests should be advantageous would be beneficial, while descendants just a generation or two distant might find themselves in egalitarian societies where physical dominance, initiative, and energy might be more likely to determine evolutionary success. I don’t mean to imply that these generalizations regarding personality-type and evolutionary success are necessarily supported by evidence. The key here is that the social milieux of successive generations could be radically different if the models of Leach and Scott are right (and the evidence brought to bear by Scott is impressive and leads me to think that the models are right). At the very least, this will reduce the average selection differential on the putative genes for personality types that are adapted to particular socio-political environments. More likely, I suspect, it will establish quite different selective regimes — say, for behavioral flexibility through strong genotype-environment interactions!

These are some of the big issues regarding genetics and the evolution of human behavior that have been bothering me recently. I’m not sure how we go about fixing this problem, but a great place to start is by fostering more collaborations between geneticists and behavioral biologists. Of course, this would be predicated on behavioral biologists’ motivation to fully understand the origin and maintenance of phenotypes and I worry that the institutional incentives for this are not in place.

I’m done now with the first week of the Spring quarter. It was a bit challenging because I had to attend the PAA meetings in Washington, DC for the latter part of the week, but Brian Wood ably covered for me on Thursday. I thought that I would use the blog as a tool for summarizing one of the key points I want students to take away from this fist week in which we discussed evolution and natural selection.

We spent a good deal of lecture time talking about adaptation. Specifically, we discussed how adaptation can serve as a foil to typology and essentialism. Adaptation is local and must be seen within its specific environmental and historical context. Adaptations are dynamic because environments are.

Adaptationist thinking is powerful, but can easily be overdone. This is why I also think it is essential to understand the mechanics of selection, something that I’m afraid is not often addressed in introductory evolutionary anthropology classes. So, in the very first lecture of class, I throw some quantitative genetics (and, thus, some math) at students. Of course, these are Stanford students, so I’m confident they can handle a little techie-ness every now and then. We specifically discuss the multivariate breeder’s equation, sometimes known as Lande‘s equation:

,

where is the change in the mean fitness of a multivariate trait, is the additive genetic variance-covariance matrix, and is the selection gradient on .

In effect, is a vector pointing in the direction of the optimal change in the phenotype. The matrix does two things to this gradient pushing toward its optimum: (1) it scales the response depending on how much additive variance there is in each trait and (2) it rotates it as a function of the covariances between traits. I won’t get too much into matrix multiplication here (this is a very nice reference too). The key point is that is a square matrix (where is the number of traits we’re looking at) the diagonal elements of which are variances and the off-diagonal elements of which, represent the covariances between traits and . Selection requires variance. Without sufficient variance, even strong selection won’t change the phenotype much between generations. But variance isn’t all there is to it. When the covariances are positive, there will be substantial indirect selection, and when they are negative, you have genetic constraints at work. Selection may be pointing in a particular direction, but the structure of the trade-offs could very easily mean that you can’t actually get there.

Let’s consider three quick (toy) examples. Say we have two traits, maybe “length” and “width” (this could be something less vague and insipid: Lande (1979) looks at brain mass and body mass in a serious two-trait example). We will assume that the selection gradient is . That is, the force of selection is twice as high on length as it is on width, but it is pretty strong and positive on both. We’ll demonstrate the effect of variance and constraint in three ways: (1) more variance in the trait under weaker selection (), (2) positive covariance between the two traits (), and (3) negative covariance between the two traits ().

The figure below plots the response to selection in the three different types of genetic architecture. The direction of selection is indicated in the grey arrow. If the variances of the two traits were equal to 1 and there were zero covariances, this is where selection would move the phenotype pair (try it). We can see that the response to selection moves toward width (the trait under weaker selection) even when covariances are zero (black arrow). Why? Because there is more variance for width than there is for length (). This effect becomes more pronounced when there is positive covariance between the traits (blue arrow) — the selection toward width is . When the covariances are negative, we see something cool (red arrow). The response to selection is small and moves (almost) entirely in the direction of length. This is because the negative covariance between length and width, when acted on by the strong selection on length, all but cancels out the positive response to selection ().

This simple demonstration shows that the response to selection can be complex. Making an argument that some trait would be under selection is not sufficient to say that it actually evolved (or will evolve) that way. Entirely plausible arguments for the direction of selection are made all the time in evolutionary anthropology. Here is one from a very important paper in paleoanthropology (Lovejoy 1981: 344):

Any behavioral change that increases reproductive rate, survivorship, or both, is under selection of maximum intensity. Higher primates rely on social behavioral mechanisms to promote survivorship during all phases of the life cycle, and one could cite numerous methods by which it theoretically could be increased. Avoidance of dietary toxins, use of more reliable food sources, and increased competence in arboreal locomotion are obvious examples. Yet these are among the many that have remained under stadong selection throughout much of the course of primate evolution, and therefore unlikely that early hominid adaptation was a product of intensified selection for adaptations almost universal to anthropoid primates.

Arguing for selection without considering trade-offs can get you into trouble. Selection in the presence of quantitative genetic constraints (or even differential variance in the traits) can produce counter-intuitive results. (Selectionists, don’t dispair. There are ways to deal with this, but it will have to wait for another post). In the case of Lovejoy’s argument, there are good reasons to think that survivorship and reproductive rate are, indeed, strongly negatively correlated. Which is under stronger selection? Which has more additive variance? How strong are the negative covariances?

When we make selectionist or adaptationist arguments, we should always keep in the back of our minds the three questions:

How strong is the force of selection?

How much variance is there on which selection can act?

How is the trait constrained through negative correlations with other traits?

I received a message the other day informing me that my series of posts of evolutionarypsychology had “hit the blue.” That is, I made the front page of Metafilter. Cool. I have to admit, I didn’t know what that meant. Now I do. I just saw evidence of my hitting the blue in my Google Reader. It’s nice to know that some people have found these posts useful.

So, I’ve been spending a bunch of time recently thinkingaboutevolutionary psychology (EP). This is a field about which I have some serious reservations for a variety of reasons both technical and philosophical. That said, I do find the constant in-fighting among human evolutionary biologists tedious and think that it’s absurdly unproductive. I am currently working on a critique of some particular aspects of contemporary thought in EP and these blog posts have helped me to get some of my thoughts in order. I am also working on trying to find common ground with researchers in a variety of different “schools” of human evolutionary studies.

Rebecca Bird and I recently wrote a short essay published in Anthropology News that defends functionalist approaches to the study of human ecology (a position that, given the reaction of the editor, is rather controversial). Given the severe length constraints we faced, we were only able to give the barest outline of the research program in human evolutionary ecology that we are trying to establish at Stanford (see this previous post for some details). This is neither the place nor the time to elaborate on the argument of the essay, but I will re-cap a couple points:

Contemporary ecological (or environmental) anthropology has ceded explanations of human behavior based on rationality to economists

Expectations of group and/or individual rationality may fail because of a failure to consider the correct objective function, individual heterogeneity, or key trade-offs

“Culture” is an amalgam of behaviors and institutions that represent responses to both past and present environments and as such is not particularly useful as a causal explanation for observed behavior

We also suggest some crazy methodological ideas like measuring things and testing multiple competing hypotheses.

The point I want to take up right now is the failure of observing the predictions of rational-actor models because of the failure to account for trade-offs. Rebecca and I had one particular trade-off in mind when we wrote this. We hypothesize that there is frequently a very general trade-off between pecuniary reward and social capital. This arises from the fact that, on the one hand, sharing (especially food-sharing) is so ubiquitous in face-to-face human groups and, on the other hand, people frequently engage in social signaling specifically through economically costly activities (see Bird and Smith (2005) for a review). It would not surprise us at all if it turned out that people were much better at solving complex social optimization problems than they are at optimizing pecuniary return.

Now, in my holiday-induced state of heightened self-reflection, it occurs to me that this argument is really not all that different from Leda Cosmides’s (1989, et seq.) suggestion that people are better at solving the Wason selection test when it is presented in terms of social contracts than when it is presented in its traditional way as a test of abstract logical reasoning abilities. Yikes! Does this mean that Rebecca Bird and I are evolutionary psychologists? No, it doesn’t. It does make me think that perhaps the time has come for détente among the different schools of thought working on evolution and human behavior. I’m hardly the first person to think this (See Eric Smith’s (2000) paper for instance). But maybe I’m the first to blog it!

My Stanford colleagues Rebecca and Doug Bird are clearly leading figures in contemporary human behavioral ecology. I will let their work and the philosophy it entails stand for itself. In what follows, I will focus on my own philosophical and methodological orientation. (Perhaps they will comment on this entry at some point…)

Martin Daly and Margo Wilson (who I think generally do excellent work) rather infamously and imperialistically claimed in a 1999 review article in Animal Behaviour that EP “encompasses work by nonpsychologists, including even those who have deliberately differentiated themselves from ‘evolutionary psychology’ as ‘evolutionary anthropologists’, ‘human sociobiologists’ and ‘human behavioural ecologists’.” This led to a rebuttal paper by three eminent Human Behavioral Ecologists (Eric Smith, Monique Borgerhoff Mulder, and Kim Hill) (Smith et al. 2000). This is an excellent paper and I heartily recommend anyone interested in evolution and human behavior read the exchange, which is freely available here and here. I will defer to the Smith et al. (2000) paper for the bulk of the arguments on why it is not reasonable to think of HBE (and other approaches) as a subset of EP, but will highlight a couple here:

HBE actually pre-dates EP as a field

Prominent EP practitioners were the ones who advocated the separation in the first place, largely on theoretical grounds

There are substantial theoretical and methodological differences that characterize the two fields

The one issue that I will take up relates to my personal sensibility with regard to science. A tenet of EP is that contemporary behavior — and the fitness outcomes of this behavior — is irrelevant for evolutionary understanding. The contention is that we should instead focus on the study of the psychological mechanisms underlying behavior. The idea that current behavior and/or fitness is irrelevant comes across indirectly in Donald Symons’s (1989) critique of “Darwinian Anthropology” and more directly and forcefully in Tooby and Cosmides’s (1990) follow-up “The Past Explains the Present: Emotional Adaptations and the Structure of Ancestral Environments.” I don’t want to come across as too much of a de Finetti-style positivist here, but I have a hard time with the idea that we should sacrifice studying observables in favor of objects that we have no hope of observing. While I don’t object to studying psychological mechanisms, I do think that since the thing we are interested in explaining is human behavior, perhaps that is what we should study.

But now I find myself confronted with the fact that I have made an EP-like argument in print (albeit Anthropology News!) as well as the very real fact that I have always found Cosmides and Tooby’s argument about social reasoning and the Wason selection test compelling. Perhaps the lesson here is that we shouldn’t be idealogues with regard to our approach to science. While I will admit a distressingly positivist love of observables (a common feature of Bayesians?), my true philosophical heritage lies in the works of Peirce, James, and Dewey. As a committed pragmatist, I am willing to at least entertain just about any theoretical or methodological position that helps me solve scientific questions.

What if every student of human behavior wrote a paper in which they adopted the approach of a contrasting school? Would this be cool or would it simply be anarchic?

There are some ways in which it is perhaps easier for me to think across these schools than some of my colleagues. My dirty little secret is that I was never really trained in any of them! My graduate training is in (nonhuman) primate behavioral ecology. One of the most influential people for my intellectual and personal development (and probably the only reason I actually got into Harvard) is Irv DeVore, a foundational figure for EP. My Ph.D. advisor Richard Wrangham, while very much a behavioral ecologist when studying chimpanzees, is clearly sympathetic to EP when studying humans. In my post-doc, I moved into more applied questions of human health and population dynamics and indirectly encountered one of the other “schools” of human evolutionary thought, namely, dual-inheritance theory. Cultural transmission models are used in health research to understand the adoption of things like modern contraception or oral rehydration therapy. As a result, I have thought a little about models of cultural transmission (a chapter that I wrote in Melissa Brown’s recent book can be found here). This is a pretty natural extension of my work in epidemic modeling and while it is not a central part of my research, I suspect I haven’t said my last on the topic (particularly not if I continue to attract clever students interested in the topic).

So, those are my thoughts du jour on the study of human behavior. The winter break is rapidly drawing to a close and pretty soon I will be back in the office and will need to get back to actual research. Hopefully, these meditations in the closing days of 2008 will have a positive influence on this research.

As the next installment in my series on evolution psychology (see previous posts here and here), I thought that I would write about some thoughts on evolutionary modules. As should be obvious from previous posts, I have serious concerns about evolutionary psychology. Nonetheless, I don’t want to repeat the knee-jerk criticisms that attended the rise of what you might call (and Symons (1989) did call) “Darwinian Anthropology.” Like Anthropology more generally, I have found that the level of discourse in human evolutionary studies tends to be particularly low and this surely hinders progress toward our presumably shared goals of understanding human behavior, the origin and maintenance of human diversity, and how people respond to social, environmental, and economic changes.

In this spirit, I am taking seriously the idea of modularity. The concept of “massive modularity” seems to be pretty central to just about any definition of modern EP and it is one of the ideas that I see as potentially most problematic. A major question that naturally arises in the analysis of cognitive modularity is: what is a module? There are two senses of modularity that you find discussed in the EP literature. For a good review of this, see Barrett and Kurzban (2006). In his highly influential (1983) book, Fodor popularized the concept of a cognitive module. A Fodorian module is characterized by reflex-like encapsulation of critical functions. It is thought to be anatomically localized, inaccessible to conscious thought and has shallow outputs. Our senses and motor systems are examples of possible Fodorian modules, as are the systems that underlie language (Machery 2007).

In contrast to the Fodorian module is the second sense of modularity found in the EP literature, the evolutionary module. Like a Fodorian module, the evolutionary module is domain-specific or informationally encapsulated. That is where the resemblance ends though. Rather than being defined by a list of attributes, an evolutionary module is characterized by function. An evolutionary module is a domain-specific cognitive mechanism that has been shaped by natural selection to perform a specific task. There is no need here to specify their characteristic operating time, the shallowness of their outputs, or their anatomical localization.

Using engineering-inspired arguments about efficiency and design, the proponents of massive modularity suggest that the brain is really a collection of domain-specific modules. These modules drive not just the reflex-like actions of our sensory-motor systems but also govern higher cognitive processes like reason, judgment, and decision-making. The brain is not, as we typically conceive it, a single organ. Rather it is a collection of special-purpose information processing organs. Needless to say, such a position has been controversial. Among the notable critics are Jerry Fodor himself, who wrote a whole book with the sarcastic title (referring to Steve Pinker’s (1997) book, How the Mind Works), The Mind Doesn’t Work That Way: The Scope and Limits of Computational Psychology. Another notable critic is David Buller, the ostensible subject of my last twoposts.

Barrett & Kurzban (2006) suggest that much of the controversy surrounding the EP concept of massive modularity arises from confusion over what is meant by a module in the EP sense. That is, critics are thinking about Fodorian modules when the advocates of massive modularity have something entirely different in mind. Maybe. I’m no expert, but the argument seems plausible for at least part of the controversy. I have my own issues with modularity but I will save that for the paper that I am writing (and for which these posts serve as sketches to hopefully help me get some thoughts straight).

One point that I will make here is a fairly orthodox criticism of modularity. In enumerating possible evolutionary modules, and noting that such modules require domain-specific input criteria, Barrett & Kurzban (2006: 630) include “systems specialized for making good food choices process only representations relevant to the nutritional value of different potential food items.” Really? I’m not one to fall back on the weak “culture complicates things” argument, but I do think there are other things — including ones potentially important for fitness — involved in food choice than the nutritional quality of a potential foodstuff. Perhaps an anecdote is in order here.

A long time ago, my wife and I were taken out to a fancy Chinese restaurant in Kota Tua, Jakarta by a colleague who wanted to impress us with his esoteric knowledge of a variety of Asian cuisines. He took the initiative and ordered for the table a range of items including tripe, jellyfish, pig trotters, and chicken feet. For a variety of complex social reasons, we felt it was in our interest to not seem like naïve rubes from America. So, we ate everything unflinchingly and with smiles on our faces. These were not things we normally would have volunteered to eat (though we now regularly get jellyfish) but the social payoffs of eating these (at the time) unappealing items outweighed whatever distaste we may have experienced.

Clearly, this is a bit of a trivial example. I nonetheless think that it highlights an extremely important aspect of human decision-making. The optimal decision in a one dimensional problem may change when one increases the dimensionality of the problem, particularly when the elements of your (vector) optimand trade-off. Sometimes the optimal nutritional choice is not the optimal choice with respect to social or cultural capital. The person’s foraging decision is presumably one that balances the various dimensions of the problem. In a less trivial example, this is what Hawkes, O’Connell and Bird and Bird are suggesting is going on with some men’s foraging decisions (summarized in this review by Bird & Smith (2005)). According to their model, men make energetically suboptimal foraging decisions in order to signal their phenotypic quality to political allies and potential mates. Food choice is thus a decision that balances the potential costs and benefits of at least three fitness-critical domains (energetics, politics, and reproduction). The same logic can be applied to that other staple of EP, mate choice. What people say they want on pen-and-paper surveys is not necessarily what they get when they actually choose a mate. The problem is that one’s choice of mate spills over into so many other domains than simply future reproduction. So it’s not simply a matter of the ideal mate being out of one’s league. Sometimes, people actually prefer a mate who does not conform to their ideal physical type.

At the very least, this point seems to require positing the existence of yet another module that integrates the outputs of various lower-level modules. Of course, this is beginning to sound more like a generalized reasoning process, the bane of EP.

There is another usage of the term “module” that I think may have some relevance to this whole discussion. In evo-devo, modularity refers to the degree that a group of phenotypic characters have independent genetic architecture and ontogeny. I will call this an “evolutionary ontogenetic module” (EOM) and contrast that with an “evolutionary cognitive module” (ECM) of EP. Sperber (2002), in his defense of massive modularity, actually discusses EOMs in passing. Pigliucci (2008) details the various, largely divergent definitions of modularity. I tend to think about EOMs the way that Wagner & Altberg (1996) do, wherein a modular set of traits is one with (1) a higher than average level of integration by pleiotropic effects (i.e., gene interactions) and (2) a higher than average level of independence from other trait sets. That is, modular architecture occurs where there are few pleiotropic genes that act across characters with different functions but more such effects falling on functionally related traits.

Modularity in the evo-devo sense is central to the evolution of complexity as well as the evolution of evolvability (the capacity of an organism to respond adaptively to selection). Do ECMs need to be EOMs? Does this and other related concepts from evo-devo help provide a means for relating the ideas of EP or HBE to their genetic architecture and ontogenetic assembly? I think so but I think an elaboration on this topic awaits a later post.

This is an ongoing series of meditations on evolutionary psychology inspired by my recent reading of David Buller’s piece inScientific American. I have been thinking quite a bit in the last year about the relationship between evolutionary psychology, human behavioral ecology, and evolutionary genetics, and maybe these ruminations will help me get my thoughts clear on these difficult topics. Caveat utilitor: these are not fully formed ideas but the blog is a useful device for organizing my sketches.

I must admit that I find myself torn on some of these debates. I am sympathetic to many of the criticisms voiced by Buller, but think that some of the rebuttals are quite compelling as well. For example, Buller is highly critical of work on child homicide by Martin Daly and Margo Wilson of McMaster University. Daly and Wilson, in a series of famous studies, suggest that child homicide (a rare event) is much more likely to be perpetrated by step-parents (including boyfriends). The explanation for why this might be relates to the existence of an anti-cuckoldry mechanism in men’s brains. Given the enormous obligate investment — generally on the part of two parents — entailed in the successful recruitment of human offspring, cuckoldry represents a potentially enormous fitness cost for human men.

In one study of child homicides in Canada between 1974 and 1990, Daly and Wilson calculated a risk-ratio that child homicides are perpetrated by step-parents vs. (putative) biological parents of 123.7. Buller suggests that such results might simply arise because of ascertainment bias in the reporting of child homicide. Specifically, he suggests that the cause of death listed on a child’s death certificate is far less likely to be homicide if the act was perpetrated by a biological parent. In support of this argument, he cites a paper by Crume et al. (2002) which compared cause-of-death as listed on the death certificate with the cause determined by a interagency multidisciplinary child fatality review team. This team reviewed child deaths in the state of Colorado and found that a substantial number of likely homicides were not reported as such. They were then able to investigate which attributes of (alleged) perpetrators made ascertainment more or less likely. They found that homicides committed by non-relatives (including boyfriends) were 8.41 times more likely to be recorded as such than were those committed by parents. Of 152 death at the hands of parents only 65 were correctly ascertained while 87 were not. For the 51 deaths attributable to non-relatives, 44 were correctly ascertained while seven were not. This yields an odds ratio of (44*87)/(65*7)=8.41 that non-relatives will be correctly ascertained compared to parents (the OR changes to 8.71 following multivariate adjustment — it is this number that is discussed in the various papers). This seems pretty damning (and suggests there are major problems detecting fatal violence against children). However, one point from this paper that Buller does not note in his critique (at least his 2005 paper in Trends in Cognitive Sciences) is that the odds of ascertainment for non-parent relatives — including step-parents — is not significantly different from unity. That is, the group that includes step-parents is as likely to be ascertained as biological parents. My understanding is that Daly and Wilson’s analysis applies to step-parents as well as boyfriends. The theory certainly predicts this.

My sense is that Buller is reaching a little too far in this critique. While I would hardly consider myself an expert on the topic, I have always thought quite highly of Daly and Wilson’s demographic work on homicide. One of my students is currently relying heavily on their Chicago mortality study published in BMJ. That is something I do have some expertise in and I think it is excellent. What I want to know is this: what is the counterfactual to the Daly & Wilson work? How many child deaths would need to be re-classified in order to have ascertainment bias be sufficient to account for their observed differences? Daly & Wilson (2007) do just this sort of counterfactual calculation. They assume that step-fathers are always caught, whereas biological fathers are never caught. According to their calculation, such a scenario would imply that there were 500 unaccounted-for paternal murders to yield the observed rates. This is where the problem comes in. There simply aren’t 500 deaths each year to children under five in Canada in that period that aren’t due to congenital defects or infectious disease. Mortality among the young is rare in developed countries. Clearly, not all of the effect that Daly & Wilson report can be attributed to ascertainment bias. There seems to be some there there.

I think that this over-reaching is a shame. The critiques that Buller levels in his recent Scientific American piece are serious and deserve to be taken seriously. Here, I specifically mean the idea that an analysis of the Pleistocene will yield significant clues for understanding the design of the human mind and that evolutionary psychology will be much use in helping us understand unique and universal human traits. The tone of this debate (on both sides) seems to preclude serious consideration of these important concerns.

As I mentioned in my previous post, I find the latter problem particularly troubling because it suggests that there are some things we can never know about human evolution in a scientific way. Depending on the question, one possible solution to this problem is something Marc Hauser used to talk about in Science B-29 at Harvard. The problem was how to use evolutionary tools to explain the unique phenomenon of human language. While human language is clearly a unique, derived trait — and therefore in a difficult position with respect to scientific explanation — there are features of human language (e.g., those described by Hockett in his design features of human language) that are shared across multiple species, making them amenable to the comparative method. If we limit ourselves to specific autapomorphies — as Buller apparently wants us to when it comes to Human Nature — then we are sunk. If we can find features of our cognition that are shared across species and look, as Darwin first suggested, at convergent solutions to similar problems across species, then we may have some hope of understanding the unique whole of human cognition. Of course, we can’t do this for cognitive features that have arisen since the Pleistocene because we only have one remnant of the hominin clade left (us).

Regarding our ability to understand the design of the human brain based on our knowledge of the environment of Pleistocene hunter-gatherers, Machery and Barrett (2006: 236) write that Pleistocene hominins experienced a “reduction in sexual dimorphism in body size due to increased pair bonding and male investment in offspring and corresponding reduction in male-male competition.” While I happen to agree with this point (and have two new papers either submitted or in prep elaborating my take on this particular phenomenon), it is, in fact, conjectural. There is nothing to stop us from forming hypotheses about the mechanisms or functional consequences of human behavior that result from this conjecture, and there might be substantial value in doing so. Nonetheless, I think it’s important to note that it is hardly certain that the cause of the reduction in sexual dimorphism among Pleistocene hominins (something we are pretty sure of) was pair bonding. I’m afraid to say that I am not the least bit confident that we will ever know this for certain.

Why do we think that Pleistocene hominins were “pair bonded”? We know that sexual size dimorphism is a correlate of mating system. Polygynous mammals tend to be sexually dimorphic. The more polygynous, the more dimorphic. Presumably, this arises through intra-male mating competition, where size matters for the outcome of agonistic encounters. As detailed in our 1999 paper, the best paleontological evidence we have suggests that there was a substantial reduction in both sexual size dimorphism and dimorphism in canine teeth (another strong correlate of polygyny among Primates) with the emergence of the genus Homo. This reduction in sexual dimorphism is attributed by many authors, ourselves included, as a signal of a change in mating system toward increased monogamy. Does monogamy necessarily mean pair-bonding? Not necessarily. (again, I do think it’s true in this case and hopefully, I will finish the paper in which I discuss the details of this argument soon) There is also the issue that humans are not much different in terms of sexual size dimorphism from chimpanzees, whose mating system is completely promiscuous. Our teeth may rescue us here. Chimpanzees are quite sexually dimorphic in their canine teeth. But how do you weigh the importance of canines as a weapon in a species that makes tools, including weapons that allow it to kill from a distance?

My point here is that there is a good deal of uncertainty about basic aspects of Pleistocene hominin behavior. This uncertainty is unlikely to ever be completely resolved. As a result, I’m not convinced that looking for clues about human behavior and the design of the human brain in the behavior of Pleistocene hominins is necessarily the most efficient of productive avenue for understanding our psychology. I don’t take the absolutist position that Buller seems to take that there is nothing to be learned about the present by studying the deep past (i.e., it is more than “pure guesswork”). I like the iterative approach of working between hypothesis generation and empirical test that Machery and Barrett describe and think that it sounds an awful lot like the process that most scientists employ in their work and it sounds like the way individuals adapt to dynamic environments.

I’ll end this ramble with a question: Do you have to be an evolutionary psychologist to believe in Human Nature? Buller seems to think so and to think that it’s a bad idea. I don’t think of myself as an evolutionary psychologist, but I do think there is such a thing as Human Nature. I am struck by the fact that despite the dizzying array of cultural diversity that is manifested by our species, a smile is a smile, embarrassment is embarrassment, and a look of consternation is a look of consternation. We might find different things amusing, mortifying, or distressing but pretty much people everywhere experience these emotions and, because of our theory of mind, recognize them in others. The work of Eckman, Eibl-Eibesfeldt, and Fernald, to name a few, is pretty compelling in this regard. Do we have a cheater-detection module that was engineered in the Pleistocene? Maybe. Honestly, I don’t care that much, but I do think that denying the existence of Human Nature is done at our collective peril.

Relentless critic of evolutionary psychology, David Buller recently wrote a piece in Scientific American outlining the critique he has developed over the last several years against this particular flavor of human evolutionary studies. The author of Adapting Minds lists four ideas from contemporary evolutionary psychology (EP) that he suggests are fallacious:

In my graduate seminar on Evolutionary Theory for the Anthropological Sciences, we read Buller’s more technical (2005) critique of EP. I find myself largely in agreement with his criticisms and, importantly, when I disagree with him, I think it is for interesting reasons.

The first of these critiques is, in my opinion, the most far-reaching and damning. The Pleistocene, the geological epoch that lasted from around 1.8 million to 10,000 years before present, takes on the role as a mythical age of creation for EP. You see, the Pleistocene represents out species “Environment of Evolutionary Adaptedness” (EEA), a concept derived from developmental psychology and particularly John Bowlby, the father of attachment theory. In the words of Tooby and Cosmides (1990: 386-387), the EEA “is not a place or a habitat, or even a time period. It is a statistical composite of the adaptation-relevant properties of ancestral environments ecounted by members of ancestral populations, weighted by their frequency and fitness-consequences.”

The key question, as Buller notes, is what would such a statistical composite look like for humans? The insight that is regularly trotted out is that humans (hominins really) were everywhere hunter-gatherers until about 10,000 years ago — and were mostly hunter-gatherers for some substantial period after that! So, what do we know about hunter-gatherers? Much to our collective loss, most of what we know about hunter-gatherers comes from the study of highly marginalized populations. This is because states, with their potential economic surpluses, large populations sizes, and hierarchical social organization (read: efficient militaries) pushed hunter-gatherers into marginal habitats throughout the world as they moved across the landscape. Nonetheless, the hunter-gatherer populations that we know about are a remarkably diverse lot. A terrific reference cataloging some of this diversity is Robert Kelly’s (1995) The Foraging Spectrum. In my specific area of interest (i.e., biodemography), Mike Gurven and Hilly Kaplan have recently written a very interesting paper on the diversity of hunter-gatherer patterns of mortality. In this figure, taken from Gurven and Kaplan’s paper, we can catch a glimpse of the variability just in hunter-gatherer demography.

Humans are clearly quite different from chimpanzees. The point of Gurven and Kaplan’s paper is that the existence of elderly within our societies is not simply an artefact of the modern industrialized world. Old-age is as much a part of the human life cycle as is childhood. Given the long potential lifespans of people in all the sampled populations, there is nonetheless a remarkable diversity in life expectancy (the average number of years lived by a person in the population) portrayed in this figure, considering that these are all groups without access to modern medicine. There are people who live in arid lands of Sub-Saharan Africa (!Kung, Hadza), South American forests (Ache, Tsimane, Yanomamo) and South American grasslands (Hiwi). Life expectancy at age 5, () varies by as much as 30%. The basic point here is that even in something as basic as age-specific schedules of mortality and fertility, different hunter-gatherer groups are very different from each other (note that the Ache and !Kung differ in their total fertility rates by a factor of nearly two).

In all likelihood, our Pleistocene ancestors, like the sample of hunter-gatherer societies discussed in Kelly (1995) or Gurven and Kaplan (2007), lived in diverse habitats, engaged in diverse economic activities within the rubric of hunting and gathering, had diverse social structures, met with diverse biotic and abiotic environmental challenges to survival and reproduction, and dealt with diverse hostile and harmonious relations with conspecifics outside of their natal groups or communities. In other words, it’s hard to imagine what neat statistical generalizations about hunter-gatherer lifeways — and the selective forces they entailed — could emerge from such diversity. People lived in face-to-face societies. People had to integrate disparate sources of information to make decisions about fundamentally uncertain phenomena. There was probably a sexual division of labor, though not necessarily the same one everywhere. There were women and men. Probably some other things too, but not that many. Robert Foley (1996) has a nice critique of what he sees as an extreme simplification of the Pleistocene hunter-gatherer lifeways under the rubric of the EEA.

Another related problem with the EEA line of thinking is this idea that somehow selection stopped when humans developed agriculture. 10,000 years, while brief in the grand scheme of things, is still not exactly evolutionary chump change. That span represents anywhere from 350-450 human generations. This is, in fact, plenty of time for selection to act. We know from genome scans done in the lab of Jonathan Pritchard, for example, that there is extensive evidence for rapid, recent selection in humans. New, complex psychological mechanisms? Probably not, but we should nonetheless not fall into the trap of thinking that somehow evolution stopped for our species 10,000 years ago.

Buller’s second fallacy (“We Know, or Can Discover, Why Distinctively Human Traits Evolved”) is a deeply difficult problem in human evolution. I’m afraid that my current thinking on this problem leads me to the same pessimistic conclusion that Buller and his colleague Jonathan Kaplan come to: There are just some things that we can’t know (scientifically) about human evolution. This arises from the fact that our species is the only member of our genus and we are separated from our sister species by nearly six million years. As Dick Lewontin first noted in 1972, despite our dizzying cultural and social diversity, we are an amazingly homogenous species genetically. I suspect that what this means is that the standard conceit of EP (one that Buller is highly critical of), that humans are everywhere the same critter, is probably true. Unique (and universal) phenomena present science with a particular explanatory challenge. Buller is spot on when he criticizes EP for wanting it both ways. On the one hand, EP sees a robust and universal human nature (an idea to which I am sympathetic, by the way). On the other, EP sees strong selection driving the evolution of diverse psychological mechanisms. The unpleasant reality is that if selection on psychological mechanisms were, in fact, that strong and pervasive, we should expect contemporary heterogeneity in the expression of such adaptations across different populations. This is a topic that University of Illinois anthropological geneticist Charles Roseman and I have talked about quite a bit and have a very slowly gestating manuscript in which we discuss this and other ideas. I know of no convincing evidence that such variation exists and for this and other reasons, I remain a steadfast skeptic of the idea that natural selection has shaped all these important psychological mechanisms independently and with precision to the tasks to which they are supposed to represent engineering solutions.

Buller’s argument for fallacy #3 (“Our Modern Skulls House a Stone Age Mind”) is, I think, a little unfair. The major argument he makes on this point is that some of our psychological mechanisms did not, in fact, arise in our Pleistocene hunter-gatherer ancestors, but are of a more ancient, primate (or even mammalian) nature. Honestly, I doubt that this point would elicit many complaints by anyone of the so-called Santa Barbara school. Sometimes critics — myself included — make a little too much of the it-all-evolved-in-the-Pleistocene bit. I think this is one example of that. Tooby and Cosmides have themselve argued that the EEA can be thought of as working at a variety of time scales. The emotional systems described by Jaak Panksepp and used by Buller in his critique — Care, Panic and Play — are all pretty basic ones for a social species. Indeed, the emotional system of panic almost certainly pre-dates complex sociality. The EEA argument, as laid out by John Tooby and Irv DeVore (1987) and then by Tooby and Cosmides (1990), is essentially one of evolutionary lag: complex adaptations to past environments are carried forward into the present. When a system retains its function, the scale of such lag can be large. Think about bilateral symmetry or the tetrapod bauplan. I think that a fair assessment of Santa Barbara style EP reveals that there is nothing contradictory about the existence of primitive (in the sense of pleisiomorphic) emotional systems in contemporary humans.

Another small point of departure between Buller’s critique and my own thinking on the matter is his discussion of David Buss‘s work on sexual jealousy. Now, I should be perfectly clear here. I happen to think that the whole sex-differences in sexual preferences thing is the most overplayed finding in all of evolutionary science. In class, I refer to this work as Men-Are-From-Mars Evolutionary Psychology. The basic idea is to take whatever tired sexual stereotype that you’d hear in a second rate stand-up comedian’s monologue, or read about in airport bookstore self-help tracts and dress it up as the scientifically proven patrimony of our evolutionary past. Ugh. No, the part of Buller’s argument with which I disagree is his apparent take on decision-making. Buller writes, “According to Pop EP, many cultural differences stem from a common human nature responding to variable local conditions.” I guess I’m not so clear as to what’s wrong with such a statement. Isn’t that really what he argues in the previous paragraphs when he suggests that women and men have a fundamentally similar reaction to sexual jealousy? On this he writes, “Instead both sexes could have the same evolved capacity to distinguish threatening from nonthreatening infidelities and to experience jealousy to a degree that is proportional to the perceived threat to a relationship in which one has invested mating effort.” An evolutionary psychology that took seriously environmental (including cultural) variability and combined it with some preferences over risk and uncertainty and a generalized calculus of costs and benefits: Now that would be interesting! Of course, I’d call that behavioral ecology.

Regarding fallacy #4 (“The Psychological Data Provide Clear Evidence for Pop EP”) more generally, I think that Buller is right on. The evidence for many of these so-called psychological adaptations is pretty weak. There is general contempt for population genetics among the smarter (and there are smart ones) evolutionary psychologists with whom I have talked and general ignorance among the less gifted. I think this contempt and/or ignorance is expressed to the detriment of scientific progress in EP. Buller’s point that cross-cultural differences are sometimes greater than inter-sexual differences in the psychological traits that are putative adaptations for sex-specific reproductive strategies, while not specifically substantiated, is pretty devastating. This is where population genetics comes in. Thinking about within vs. between population variance is a very important step in understanding the evolutionary forces at work.

The complex organ that is the human brain is certainly the result of selection. As George Williams reminds us, selection is the only evolutionary mechanism that can produce this type of complexity. So, like Buller, I agree that there must be an evolutionary psychology. Our various complaints are with the evolutionary psychology that Buller labels “Pop EP.” It’s all too easy to be critical. Developing scientific theories for phenomena as complex as those surrounding the evolution of our species is a difficult task and takes ingenuity, courage, and, of course, thick skin. Among the various practitioners of EP of whom Buller is particularly critical, I think that John Tooby and Leda Cosmides are smart people who manifest all these qualities. A fallacy of contemporary discourse — one that is all too easily seen in anthropological meetings — is that people who disagree intellectually must hold each other in contempt or otherwise dislike each other. I disagree with much of current EP but I also think there are some interesting ideas among practitioners of EP, once we get beyond the trite Men-Are-From-Mar/Women-Are-From-Venus stereotypes.

Detailing where I think the action is in an interesting evolutionary psychology is at the very least another long blog post. Some areas that I think are promising and/or under-studied include: detailed analyses of cultural transmission dynamics, understanding how people integrate diverse types of information to form decisions with fitness consequences, and understanding how people weigh risk and uncertainty. I have a lot more to say on these topics, so I think it will have to wait for future posts…

Olivia Judson has written another installment in her series celebrating Charles Darwin. In this one, she suggests that we should lose the term “Darwinism” and all its variants. I think that she argues convincingly that labeling the scientific enterprise of modern evolutionary biology as “Darwinism” implies that the field is static, indeed, “that the subject hasn’t changed much in the 149 years since the publication of the Origin.” Of course, nothing could be further from the truth and the obsession with questions of the form “Was Darwin Right About X?” plays into the hands of anti-rationalist, anti-science creationists.

Frequently, I have been bothered by the cult of Darwin that one finds among a certain kind of evolutionary thinker and it’s nice to see Judson calling this out.

There is an interesting dynamic that played out in the area of human behavioral biology in the late 1980s and early 1990s. At the time, there was a feud developing between scientists who studied the present-day consequences of variation in human behavior and those more interested in the design of the organ that leads to behavior, the brain. In a provocative paper written in 1989, Donald Symons of the University of California Santa Barbara suggested that “adaptive design is usually manifested at the psychological rather than at the behavioral level, that measuring reproductive differentials is at best an inefficient and ambiguous way to illuminate adaptation, and that Darwin’s theory of natural selection sheds light on human affairs only insofar as it promotes understanding of the psychology that underpins these affairs.” (there’s that ownership of natural selection again) Needless to say, this paper did not go over well with people who actually chose to measure the present-day consequences of behavior (e.g., on reproductive success) and a bit of a flame war broke out in the pages of the journal Ethology & Sociobiology (the official publication of the Evolution and Human Behavior Society and later to be renamed Evolution and Human Behavior).

What is so interesting about this debate is how, in good segmentary fashion, the two sides desperately tried to claim Darwin as the founding mythological patriarch of their lineage. A science true to Darwin’s legacy would variously study behavior or study psychology depending upon whether one was a Darwinian Anthropologist or a Darwinian Psychologist (Symons’s terms, though I should note that to this day, at least a plurality of evolutionary psychologists reside professionally in anthropology departments). This debate continues, albeit a little less raw. I list a number of key papers in this debate below. We read these in my graduate seminar on evolutionary theory in the anthropological sciences.

So I support Judson’s call to drop the term “Darwinism” (or “Darwinian”) from our regular scientific vocabulary. As she cleverly argues, we don’t refer to fixed wing aeronautical engineering as “Wrightian” aeronautics, despite the fact that the field was established by the Wright brothers. Use of the patronym plays into the hands of creationists. It also makes it too easy to forget that evolution is effected by more than simply “Darwin’s” natural selection. There is (the other) “Wrightian” genetic drift. Or mutation. Or even something as prosaic as migration (dare I call it “Cavalli-Sforzian”?). Science should strive to transcend the cult of personality. I, for one, would like to see less political and religious jockeying to see which tradition can be more true to its mythological “Darwinian” patriarch and more focus on actually doing science. But I guess that just shows that I remain naïve about human nature.

I was interested to browse through a paper by Buunk et al. in the most recent issue of Evolution and Human Behavior in which the authors report the results of psychological experiments exploring the differential relationship between height and sexual jealousy in women and men. The authors predicted that (self-reported) sexual jealousy would decline with increasing height in men and that women of average height would report the lowest levels of sexual jealousy. The theory driving these predictions is that higher-status, more attractive individuals should be less jealous on average because they are better able to prevail over would-be competitors and, presumably, if they experience partner infidelity, they can always find another partner. The authors cite the abundant evidence for increased social dominance in taller men and suggest the relationship between women’s attractiveness and height is quadratic, with women of average height being most attractive. One hundred women and 100 men were asked question, “In general, how jealous are you in your current relationship?” Responses fell on a six point scale ranging from (1) “not jealous” to (6) “morbidly jealous”. The authors’ results apparently support their hypotheses. So here are the two figures that they use to show that (1) jealously declines linearly with height in men and (2) is quadratic for women, with average-height women least jealous. The first figure is for men:

The second figure is for women:

Hmmm. I don’t know if I would rest much on the interpretation of that figure as being “quadratic.” It seems entirely possible that the curve is driven simply by the sparseness of the tails. There are fewer women of extreme height, either tall or short and this allows a few influential points to leverage the line up at the ends. Think about the upper 95% confidence interval of a linear regression line. Doesn’t look that different from their figure 2, no? This makes me wonder how robust the relationship is. For example, if we were to bootstrap replicate samples (with replacement) and re-fit the quadratic form, how many would have a significant at some conventional level (e.g., p<0.05)? There is also the question of whether this quadratic curve fits better than a linear relationship. One could test the two nested models using a likelihood ratio test.

Then there is the question of confounding variables. At the very least, it seems that one would want to control for age of the actors, duration of relationship, and quite possibly other measures of wealth or status. It seems reasonable to posit that being extremely wealthy would modify the degree of sexual jealousy experienced by a man of average height, for instance.